ChatGPT in Drug Discovery Process

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Ravi Kiran Ammu V.V.V.; Kumari Garikapati Kusuma; Krishnamurthy Praveen T.

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Journal Paper

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Journal: Advanced Pharmaceutical Bulletin Year:2024 | Volume:14 | Issue:1 Page(s): 5-6

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Title

ChatGPT in Drug Discovery Process

Author(s)

Ravi Kiran Ammu V.V.V. | Kumari Garikapati Kusuma | Krishnamurthy Praveen T. | Issue Writer Certificate

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Abstract

Dear Editor, Over the decades, advancements in technological fields have greatly reshaped the drug development process in pharmaceutical companies. This drive in drug development process is due to an increase in computed generated prediction models and pre-screening of new chemical entities.1 In recent years, artificial intelligence such as ChatGPT has made its new entry, attracting many biopharmaceutical scientists, globally. ChatGPT is a large language model developed by OpenAI that is trained on a vast corpus of text data. It has been used in a variety of applications, including natural language processing, language translation, and text generation. One of the most promising applications of ChatGPT in the field of drug discovery is its ability to generate new chemical compounds. This is done by training the model on a dataset of known compounds and their properties.2 Once trained, the model can generate new chemical compounds that are similar to the compounds in the dataset. This can be useful in the drug discovery process as it can help to identify new compounds that have the potential to be developed into drugs. Another application of ChatGPT in drug discovery is its ability to predict the properties of new compounds. By training the model on a dataset of known compounds and their properties, it can predict the properties of new compounds that it has never seen before.2 This can be useful in the drug discovery process as it can help to identify compounds that have the potential to be developed into drugs

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